> For the complete documentation index, see [llms.txt](https://2025.istvs.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://2025.istvs.org/submissions/papers/2469.md). # 2469 - TERRA-V TOOLCHAIN: VIRTUAL VALIDATION AND OPTIMIZATION OF AUTONOMOUS VEHICLES IN UNPAVED TERRAIN {% hint style="info" %} Paper presented at ISTVS 2025 | 55th Conference of the International Society for Terrain-Vehicle Systems {% endhint %} **Authors:** *Gerhard Skoff, Daniel Hassler, Gernot Hasenbichler* **Keywords:** Autonomous Systems; Validation; Offroad-Mobility; Simulation **Abstract:** To ensure safe and robust autonomous offroad-operation, specific challenges must be managed, including robust terrain-specific obstacle detection. Virtual approaches have the potential to significantly shorten development time and effort. Adequate methods need to consider changing environmental conditions, as e.g. changes of the vegetation during the seasons of the year as well as weather. To manage all those requirements, a modular simulation platform has been developed. The toolchain consists of six independent and flexible modules, which are all linked together to conduct simulations seamlessly and with best correlation to real world: 1. Vehicle-specific multibody dynamic simulation module of the vehicle, which can be derived from different multibody dynamic simulation tools, whereby a mathematical soft-soil model applies, 2. A terrain model, which utilizes a comprehensive set of specifically designed terrain elements, and which undergo AI-supported modifications, e.g. darkness, fog or rain during the validation process, 3. A sensor module, which can operate with different kinds of active and non-emitting sensors. Sensor selection and arrangement on the vehicle are optimized in the virtual sensor lab, 4. An autonomous algorithm, which is the system-under-test (SuT) and which gets optimized and validated, 5. Set of terrain-specific KPI’s, which define application-specific boundaries and qualification criteria, 6. A terrain-specific scenario database, where ontology-based automated offroad-scenarios are generated. The sensor model and SuT get integrated into the Vehicle model, and the vehicle is executing the automatically generated, ontology-based testcase-combinations. Application-specific KPI’s are calculated and compared with target values. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://2025.istvs.org/submissions/papers/2469.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.